Biology subjects

He, N.

Publications and source records attributed to He, N..

At least 19 recordsLinked to original sources

bioRxiv2026

Complete Genomes of Cultivated Gut Bacteria Reveal Mobile Genetic Element-Driven Functional Diversity with Therapeutic Implications

Cultivated bacterial isolates are essential for elucidating gut microbiota functions, yet reliance on fragmented draft genomes and limited mobile genetic element (MGE) annotation has constrained high-resolution analyses. Here, we present the Cultivated Complete Genome Reference (CCGR), a comprehensive compendium of 1,150 fully circularized human gut bacterial genomes. Overcoming draft limitations, CCGR achieves chromosome-scale resolution and reveals distinct evolutionary strategies shaping gene topological organization in response to bacterial growth. Furthermore, we decode the dynamic landscape of MGEs, demonstrating that broad-host-range phages follow strict positional patterns by integrating at conserved chromosomal hotspots flanked by nutrient transporter loci. Importantly, we provide mechanistic in vivo evidence that accessory genomic elements drive strain-level functional heterogeneity. Specifically, the plasmid-encoded scrK gene in Levilactobacillus brevis involved in fructose catabolism is required to mitigate fructose-diet-exacerbated colitis. Collectively, CCGR establishes a framework linking chromosomal architecture and MGEs to bacterial evolution and host health, enabling precise, strain-resolved functional investigations.

microbiology↗

bioRxiv2025

Robust brain complexity measurement using T2* informed multivariate sample entropy from multi-echo BOLD fMRI

Sample entropy is a useful tool to analyze resting-state fMRI data and evaluate the complexity of neural activity. However, sample entropy computed from conventional BOLD signals is not highly resistant to artifacts. In contrast, T2* may be more sensitive to certain neural-related changes, and directly incorporating T2* information enables the detection of features that are often lost in BOLD-only sample entropy due to noise influences. To further improve the robustness and reliability of complexity estimation, we introduce a multivariate sample entropy approach that incorporates T2* signals derived from multi-echo BOLD signal. We applied this method to compare a cohort of 23 elder adults and 12 younger adults, and observed significant group differences in several brain regions. Notably, the proposed method yielded more pronounced group differences than conventional sample entropy computed without T2* information. Moreover, in regions with reduced neural activity due to ischemia, as well as in ventricular areas, our approach demonstrated superior performance. These results indicate that the proposed method enhances the ability to characterize the complexity of neural activity.

biophysics↗

bioRxiv2025

DeepHalo: Deep Learning-Powered Exploration of Halogenated Metabolites Uncovering Antibacterial Depsipeptides

In the omics era, confident high-throughput analytical tools are crucial for the efficient identification of metabolites. Here, we present DeepHalo, a deep learning-integrated and hierarchically optimized workflow designed for high-throughput exploration of halogenated metabolites from high-resolution mass spectrometry-based metabolomics. DeepHalo leverages deep learning models combined with a comprehensive scoring to enhance the reliability of halogen predictions. It integrates PyOpenMS for fast isotope pattern detection and incorporates a halogen-based dereplication algorithm with GNPS molecular networking to efficiently exploit and annotate halogenates from complex biological matrices. To validate its performance, DeepHalo was applied to explore halogenated metabolites from 1,296 microbial culture crude, leading to the discovery of six families of structurally diverse halogenated molecules. This included a new class of cyclic depsipeptides, aglomycins A-E, featuring rare 3-chloroanthranilic acid and/or epoxyvaline blocks. Additionally, a plausible biosynthetic pathway of aglomycins was proposed through bioinformatics analyses and targeted gene knockout experiments. Bioassays revealed that aglomycin A exhibits synergistic antibacterial activity with linezolid against vancomycin-resistant Enterococcus faecium (VRE) both in vitro and in vivo. We envision that DeepHalo (freely available at https://github.com/xieyying/DeepHalo) will become a powerful tool for accelerating the discovery of halogenated "dark matter".

biochemistry↗

bioRxiv2025

Unraveling the mechanism of 1-deoxynojirimycin (DNJ) accumulation: the role of SWEET3 in mulberry chloroplasts

Transporters are crucial for the accumulation and secretion of plant metabolic products. 1-Deoxynojirimycin (DNJ), a natural compound widely distributed in nature and known for its medicinal properties, has production limitations in microorganisms and herbaceous plants. Mulberry leaves, being easy to harvest and growing rapidly, are the main source of DNJ. However, the current production from mulberry is insufficient to meet the demand. Improving DNJ content in mulberry and thereby reducing production costs is a significant challenge. We first used a green fluorescent tag to visualize the localization of DNJ and found that DNJ highly accumulates in the chloroplasts of mulberry leaves but not in callus tissue. The sugar transporter gene SWEET3, which is highly expressed in mulberry leaves but not in callus, was shown to have DNJ transport capability. Molecular docking analysis revealed that the acidic amino acid residues E68 and D126 in the SWEET3 protein are potential binding sites for DNJ, and both neutral and basic mutations at these sites significantly reduced the ability to DNJ-transporting ability of SWEET3. Furthermore, transient overexpression or RNA interference of SWEET3 in mulberry leaves significantly increased or decreased DNJ content, respectively. Similarly, stable overexpression of the SWEET3 in mulberry hairy roots led to an enhancement in DNJ content within the roots. Our results demonstrated that SWEET3 is essential for DNJ accumulation in mulberry. The study represents a breakthrough in increasing DNJ yield in mulberry through the key role of transporters and identify specific molecular targets required for developing mulberry germplasm with increased DNJ levels.

plant biology↗

bioRxiv2025

The Binary Cellular Biology of Human Growth I Quantifying the Creation and Growth of the Body and its Parts

Assessing and understanding the Growth and Development of animals generally, and of human fetuses specifically, provides essential information for the management of the health of the newborn and its mother. Here we show that a consideration of the formation of the body, in units of numbers of cells, N, and the change in these numbers by the binary either/or decisions of cells to divide or not, an approach we call Binary Cellular Analysis, provides new insights and new equations for quantifying the growth and development of the body and its parts. These equations include: 1) The Binary Cellular Universal Growth Equation, which captures growth from conception to adulthood, and provides a method for biologically-based, data-driven, Growth Curves; 2) The Binary Cellular Universal Mitotic Fraction Equation, which lies within the Binary Cellular Universal Growth Equation, and captures the mechanism of growth to adult size, control of cell division; 3) The Binary Cellular Allometric Growth Equation, which captures the creation and growth of the Tissues, Organs, and Anatomical Structures of the body, and how the embryo creates each Body Part from a Single Founder Cell; and, 4) Binary Cellular Estimated Fetal Weight Equations, derived from the Binary Cellular Allometric Growth Equation, which captures the relationship between Ultrasound Measurement and the Size of the body as a whole. These equations capture the developmental process of Cellular Selection, resulting from Differential Cellular Proliferation, which molds the formation of the body from a single fertilized ovum into a multicellular animal. The parameters of these equations both capture the differences in Size and Growth between animals across the taxonomic spectrum, and between human fetuses, as well as identify the individual mechanisms of mitosis that drive Growth and Development. From the Binary Cellular Universal Growth Equation, the Growth of human fetuses can be measured, thus providing a much-needed tool for understanding the biological forces that cause a fetus to grow to Small, Average, or Large Size at birth, for providing the basis of biologically-based, data-driven, Growth Curves, and for assisting the management of the obstetric care of the fetus and its mother.

developmental biology↗

bioRxiv2023

A continental-scale analysis reveals the latitudinal gradient of stomatal density across amphistomatous species: Evolutionary history vs. present-day environment

Amphistomy is a potential method for increasing photosynthetic rate; however, latitudinal gradients of stomatal density across amphistomatous species and their drivers remain unknown. Here, the adaxial stomatal density (SDad) and abaxial stomatal density (SDab) of 486 amphistomatous species-site combinations, belonging to 32 plant families, were collected from China, and their total stomatal density (SDtotal) and stomatal ratio (SR) were calculated. Overall, these four stomatal traits did not show significant phylogenetic signals. There were no significant differences in SDab and SDtotal between woody and herbaceous species, but SDad and SR were higher in woody species than in herbaceous species. Besides, a significantly positive relationship between SDab and SDad was observed. We also found that stomatal density (including SDab, SDad, and SDtotal) decreased with latitude while SR increased with latitude, and temperature seasonality was the most important environmental factor driving it. Besides, evolutionary history (represented by both phylogeny and species) explained about 10-22 fold more of the variation in stomatal traits than the present-day environment (65.2%-71.1% vs. 2.9%-6.8%). Our study extended our knowledge of trait-environment relationships and highlighted the importance of evolutionary history in driving stomatal trait variability.

ecology↗

bioRxiv2023

Genetic Dependence and Genetic Diseases

The human life depends on the function of proteins that are encoded by about twenty-thousand genes. The gene-disease associations in majority genes are unknown and the mechanisms underlying pathogenicity of genes/variants and common diseases remain unclear. We studied how human life depends on the genes, i.e., the genetic-dependence, which was classified as genetic-dependent nature (GDN, vital consequence of abolishing a gene), genetic-dependent quantity (GDQ, quantitative genetic function required for normal life), and genetic-dependent stage (GDS, temporal expression pattern). Each gene differs in genetic-dependent features, which determines the gene-disease association extensively. The GDN is associated with the pathogenic potential/feature of genes and the strength of pathogenicity. The GDQ-damage relation determines the pathogenicity of variants and subsequently the pathogenic genotype, phenotype spectrum, and inheritance of variants. The GDS is mainly associated with the onset age/evolution/outcome and the nature of genetic disorders (disease/susceptibility). The varied and quantitative genetic-dependent feature of genome explains common mild phenotype/susceptibility. The genetic-dependence discloses the mechanisms underlying pathogenicity of gene/variants and common diseases. One sentence summaryGenetic dependent feature differs in genes and determines pathogenicity of genes/variants and the clinical features of genetic diseases.

genetics↗

bioRxiv2023

Selective inhibition of OSBP blocks retrograde trafficking by inducing partial Golgi degradation

Sterol-binding proteins are important regulators of lipid homeostasis and membrane integrity; however, the discovery of selective small molecule modulators can be challenging due to structural similarities in the sterol binding domains. We report the discovery of highly potent and selective inhibitors of oxysterol binding protein (OSBP), which we term oxybipins. Sterol-containing chemical chimeras aimed at identifying new sterol binding proteins by targeted degradation, led to a significant reduction in Golgi-associated proteins. The degradation was found to occur at lysosomes, concomitant with changes in general protein glycosylation, indicating that the degradation of Golgi proteins was a downstream effect. By establishing a sterol transport protein biophysical assay panel, we discovered that the oxybipins potently inhibited OSBP, resulting in blockage of retrograde trafficking and attenuating Shiga toxin toxicity. As the oxybipins do not target any other sterol transporters tested, we advocate their use as chemical tools to study OSBP function and therapeutic relevance.

cell biology↗

bioRxiv2021

Contrasting adaptation and optimization of stomatal traits across communities at continental-scale

The maximum stomatal conductance (g), a major anatomical constraint on plant productivity, is a function of the stomatal area fraction (f) and stomatal space-use efficiency (e). However, f and g have been considered as equivalents, with e rarely considered, and their adaptation to the environment and their regulation of ecosystem productivity are unclear. Here, we analyzed the community-weighted mean, variance, skewness, and kurtosis of stomatal traits from tropical to cold-temperature forests. The variance of g and f was higher for arid sites, indicating greater functional niche differentiation, whereas that for e was lower, indicating convergence in efficiency. Besides, when other stomatal trait distributions remained unchanged, increasing kurtosis but decreasing skewness of g would improve ecosystem productivity, and f showed the opposite patterns. These findings highlight how the relative importance and equivalence of inter-related traits can differ at community scale.

ecology↗

bioRxiv2021

How Our Cells Become Our Selves: The Cellular Phylodynamic Biology of Growth and Development

Our lives begin with 1 cell, then 2, then 4, then the trillion cell adult, comprised of cell lineages, tissues, organs. How does this occur? Examination in numbers of cells, N, Cellular Phylodynamics, revealed two previously unappreciated processes: UNI-GROWTH, the slowing of growth that occurs as we become larger, caused by fewer cells dividing, captured by the Universal Mitotic Fraction and Universal Growth Equations, with accuracy confirmed for 13 species, including nematodes, mollusks, and vertebrates; and ALLO-GROWTH, the creation of body parts from Founder Cells, captured by the Cellular Allometric Growth Equation, which describes mitotic expansion by Cell-Heritable change in the Cell Cycle Time. These equations can generate cell lineage approximations, bringing the power of coalescent theory to developmental biology.

developmental biology↗

bioRxiv2021

Scaling between stomatal size and density in forest plants

The size and density of stomatal pores limit the maximum rate of leaf carbon gain and water loss (gmax) in land plants. The limits of gmax due to anatomy, and its constraint by the negative correlation of stomatal size and density at broad phylogenetic scales, has been unclear and controversial. The prevailing hypothesis posits that adaptation to higher gmax is typically constrained by geometry and/or an economic need to reduce the allocation of epidermal area to stomata (stomatal-area minimization), and this would require the evolution of greater numbers of smaller stomata. Another view, supported by the data, is that across plant diversity, epidermal area allocated to guard cells versus other cells can be optimized without major trade-offs, and higher gmax would typically be achieved with a higher allocation of epidermal area to stomata (stomatal-area increase). We tested these hypotheses by comparing their predictions for the structure of the covariance of stomatal size and density across species, applying macroevolutionary models and phylogenetic regression to data for 2408 species of angiosperms, gymnosperms, and ferns from forests worldwide. The observed stomatal size-density scaling and covariance supported the stomatal-area increase hypothesis for high gmax. A higher gmax involves construction costs and maintenance costs that should be considered in models assessing optimal stomatal conductance for predictions of water use, photosynthesis, and water-use efficiency as influences on crop productivity or in Earth System models.

plant biology↗

bioRxiv2020

Revisiting the phosphotyrosine binding pocket of Fyn SH2 domain led to the Identification of novel SH2 superbinders

Protein engineering through directed evolution is an effective way to obtain proteins with novel functions with the potential applications as tools for diagnosis or therapeutics. Many natural proteins, largely antibodies as well as some non-antibody proteins, have undergone directed evolution in vitro in the test tubes in the laboratories around the world, resulted in the numerous protein variants with novel or enhanced functions. In this study, we constructed a Fyn SH2 variant library by randomizing the 8 variable residues in its phosphotyrosine (pTyr) binding pocket. Selection of this library by a pTyr peptide from MidT antigen led to the identification of SH2 variants with enhanced affinities to the peptide, compared to the wild type SH2, by EC50 assay. Fluorescent polarization (FP) was then applied to quantify the binding affinity of the newly identified SH2 variants. As a result, three SH2 variants, named V3, V13 and V24, have comparable binding affinities with the previously identified SH2 triple-mutant superbinder (refer to Trm). Biolayer Interferometry (BLI) assay was employed to disclose the kinetics of the binding of these SH2 superbinders, in addition to the wild type SH2, to the phosphotyrosine peptide. The results indicated that all the SH2 superbinders have two-orders increase of the dissociation rate when binding the pTyr peptide while there was no significant change in their associate rates. The previously identified SH2 superbinder Trm as well as the V13 and V24 discovered in this study have cross-reactivity with the sulfotyrosine (sTyr) containing peptide while the wild type SH2 does not. Intriguingly, though binding the pTyr peptide with comparable affinity with other SH2 superbinders, the V3 does not bind to the sTyr peptide, implying it binds to the pTyr peptide with a different pattern from the other superbinders. The newly identified superbinders could be utilized as tools for the identification of pTyr-containing proteins from tissues under different physiological or pathophysiological conditions and may have the potential in the therapeutics.

biochemistry↗

bioRxiv2020

Resolving a Systematic Error in STARR-seq for QuantitativeEnhancer Activity Mapping

STARR-seq assesses millions of fragments in parallel measuring enhancer activity quantitatively. Here we show that STARR-seq is critically flawed with a systematic error in the cells of Arabidopsis thaliana (A. thaliana). Large amount of self-transcripts (STs) is lost during reverse transcription because these STs are polyadenylated after alternative polyadenylation sites (APAS) inside the test sequences. We solved this problem by using specially designed primer and recovered self-transcribed sequences independent from the PAS usage. In A. thaliana, we identified active enhancers and also enhancers quiescent in their endogenous genomic loci. Different from traditional STARR-seq identified enhancers, enhancers identified by new method are highly enriched in sequences proximal to the 5 and 3 ends of genes, and their epigenetic states correlate with gene expression levels. Our solution applies to methods based on self-transcript quantification. In addition, our results provide an invaluable functional enhancer activity map and insights into the functional complexity of enhancers in A. thaliana.

genetics↗

bioRxiv2020

Systematic Chromatin Architecture Analysis in Xenopus tropicalis Reveals Conserved Three-Dimensional Folding Principles of Vertebrate Genomes

Metazoan genomes are folded into 3D structures in interphase nuclei. However, the molecular mechanism remains unknown. Here, we show that topologically associating domains (TADs) form in two waves during Xenopus tropicalis embryogenesis, first at zygotic genome activation and then as the expression of CTCF and Rad21 is elevated. We also found TAD structures continually change for at least three times during development. Surprisingly, the directionality index is preferentially stronger on one side of TADs where orientation-biased CTCF and Rad21 binding are observed, a conserved pattern that is found in human cells as well. Depletion analysis revealed CTCF, Rad21, and RPB1, a component of RNAPII, are required for the establishment of TADs. Overall, our work shows that Xenopus is a powerful model for chromosome architecture analysis. Furthermore, our findings indicate that cohesin-mediated extrusion may anchor at orientation-biased CTCF binding sites, supporting a CTCF-anchored extrusion model as the mechanism for TAD establishment.

genetics↗

bioRxiv2020

MMS2plot: an R package for visualizing multiple MS/MS spectra for groups of modified and non-modified peptides

A large number of post-translational modifications (PTMs) in proteins are buried in the unassigned mass spectrometric (MS) spectra in shot-gun proteomics datasets. Because the modified peptide fragments are low in abundance relative to the corresponding non-modified versions, it is critical to develop tools that allow facile evaluation of assignment of PTMs based on the MS/MS spectra. Such tools would preferably have the ability to allow comparison of fragment ion spectra and retention time between the modified and unmodified peptide pairs or group. Herein, we describe MMS2plot, an R package for visualizing peptide-spectrum matches (PSMs) for multiple peptides. MMS2plot features a batch mode and generates the output images in vector graphics file format that facilitate evaluation and publication of the PSM assignment. We expect MMS2plot to play an important role in PTM discovery from large-scale proteomics datasets generated by LC (liquid chromatography)-MS/MS. The MMS2plot package is freely available at https://github.com/lileir/MMS2plot under the GPL-3 license.

bioinformatics↗

bioRxiv2019

Obesity Potentiates TH2 Immunopathology via Dysregulation of PPAR

How obesity affects immune function is not well understood. Clinically, obesity is strongly associated with severe TH2 immunopathology1-3, though the physiological, cellular, and molecular underpinnings of this association remain obscure. Here, we demonstrate that obese mice are susceptible to severe atopic dermatitis (AD), a major manifestation of TH2 immunopathology and disease burden in humans4,5. Mechanistically, we show that dysregulation of the nuclear hormone receptor (NHR) PPAR{gamma} (peroxisome proliferator-activated receptor gamma) in T cells is a causal link between obesity and the increased TH2 immunopathology. We find that PPAR{gamma} oversees a cellular metabolic transcriptional program that restrains nuclear gene expression of the chief TH2 priming and effector cytokine interleukin-4 (IL-4). Accordingly, thiazolidinediones (TZDs), potent PPAR{gamma} agonists, robustly protect obese mice from TH2 immunopathology. Collectively, these findings establish PPAR{gamma} as a molecular link between obesity and TH2 immune homeostasis and identify TZDs as novel therapeutic candidates for TH2 immunopathology. Fundamentally, these findings demonstrate that shifting physiologic metabolic states can shape the tone of adaptive immune responses to modulate differential disease susceptibility.

immunology↗

bioRxiv2019

Amplification-free Library Preparation Improves Quality of Hi-C Analysis

PCR amplification of Hi-C libraries introduces unusable duplicates and results in a biased representation of chromatin interactions. We present a simplified, fast, and economically efficient Hi-C library preparation procedure that generates sufficient non-amplified ligation products for deep sequencing from 30 million Drosophila cells. Comprehensive analysis of the resulting data indicates that amplification-free Hi-C preserves higher complexity of chromatin interaction and lowers sequencing depth dramatically for the same number of unique paired reads. For human cells which has a large genome, this method recovers an amount of ligated fragments enough for direct high-throughput sequencing without amplification on as low as 250 thousand of cells. Comparison with published in situ Hi-C on millions of human cells reveals that amplification introduces distance-dependent amplification bias, which results in increasing background noise level against genomic distance. With amplification bias avoided, our method may produce a chromatin interaction network more faithfully reflecting the real three-dimensional genomic architecture.

genomics↗

bioRxiv2018

Global Quantitative Mapping of Enhancers in Rice Genome by STARR-seq

Identification of enhancers has been a challenge in plants. STARR-seq measures enhancer activity of millions fragments in parallel. Here we present a global map of rice enhancers quantitatively determined using STARR-seq. Most enhancers are mapped within genes, especially at the 5 untranslated regions (5 UTR) and the coding sequences. Silent and low expressed genes in genomic regions enriched with transposable elements (TEs) are frequently found containing proximal enhancers. Analysis of enhancer epigenetic features at their endogenous loci revealed that most enhancers do not co-localize with DNase I hypersensitive sites (DHSs) and are lack of H3K4me1. Clustering enhancers by their epigenetic modifications revealed that about 40% of identified enhancers carry one or more epigenetic marks. Repressive H3K27me3 is frequently enriched with positive marks of H3K4m3 and/or H3K27ac, which together may bookmark poised enhancers. Intergenic enhancers were predicted based on the location of DHS relative to genes, which overlap poorly with functionally identified enhancers. In summary, enhancers were quantitatively identified by functional analysis in a model plant genome, which provides a valuable resource for further mechanistic studies in different biological contexts.

genomics↗